example of data cube vocabulary - web.imsi.athenarc.gr · instance of the class rdfs:class and that...

Institute for the Management of Information Systems

RC “Athena”

Publishing Statistical Data as Linked Data

«The RDF Data Cube Vocabulary»

Open Data Day 2013@ Athens

George Papastefanatos

Irene Petrou

Data Cube Vocabulary

• Source:

http://www.w3.org/TR/2012/WD-vocab-data-cube-20120405/

• W3C Working Draft 05 April 2012

• The Data Cube Vocabulary is based on the following existing RDF

vocabularies:

• SKOS for concept schemes

• SCOVO for core statistical structures

• VoiD for data access

• FOAF for organisations

• Dublin Core Terms for metadata












http://www.w3.org/2004/02/skos/

http://sw.joanneum.at/scovo/schema.html

http://rdfs.org/ns/void-guide

http://xmlns.com/foaf/0.1/

http://purl.org/dc/terms/

http://purl.org/dc/terms/

Outline of the Data Cube Vocabulary

Basic Steps

1. Define the prefixes to be used

2. Publish your schema

◦ Define the dimension(s) – used to identify the observations (ex. time, region), what the observation applies to

◦ Define the measure(s) – the phenomenon being observed

◦ Define the attribute(s) - unit of measure

◦ Define the DSD (attach components)

3. Publish your data

◦ Define the Dataset (attach DSD)

◦ Define Observations – the actual data (ex. the values in the cells of a table)

4. Including Slices (views) on your data

◦ Define SliceKey(s) - the fixed dimensions

◦ Define the DSD (attach SliceKey(s))

◦ Define the Dataset (attach Slices to be defined)

◦ Define Slices and Observations

5. Selecting appropriate URIs

Example of Data Cube Vocabulary Source: StatsWales Report number 003311

Topic of the Data Set: Life expectancy broken down by region (unitary

authority), sex and time.

• Three dimensions:

1. Time period

2. Region

3. Sex

• Measure: Each observation represents the life expectancy for that

population – a single measure which corresponds to all data set

• Attribute: Years (the units of the measured values)

2004-2006 2005-2007 2006-2008

Male Female Male Female Male Female

Newport 76.7 80.7 77.1 80.9 77.0 81.5

Cardiff 78.7 83.3 78.6 83.7 78.7 83.4

Monmouthshire 76.6 81.3 76.5 81.5 76.6 81.7

Merthyr Tydfil 75.5 79.1 75.5 79.4 74.9 79.6

Prefixes

@prefix eg: <http://example.org/life-expectancy#>.

@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .

@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .

@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .

@prefix sdmx: <http://purl.org/linked-data/sdmx#> .

@prefix sdmx-concept: <http://purl.org/linked-data/sdmx/2009/concept#> .

@prefix sdmx-dimension: <http://purl.org/linked-data/sdmx/2009/dimension#> .

@prefix sdmx-attribute: <http://purl.org/linked-data/sdmx/2009/attribute#>

@prefix sdmx-measure: <http://purl.org/linked-data/sdmx/2009/measure#> .

@prefix qb: <http://purl.org/linked-data/cube#> .

Components definition

All dimensions, attributes and measures are components

Time:

• Reuse of Predefined concept in the SDMX-COG, refPeriod

• To represent the time period itself it would be convenient to use the

data.gov.uk reference time service. Example and more information on time

intervals can be found at:

http://www.epimorphics.com/web/wiki/using-interval-set-uris-statistical-data

eg:refPeriod a rdf:Property, qb:DimensionProperty; rdfs:label "reference period"@en; rdfs:subPropertyOf sdmx-dimension:refPeriod; rdfs:range interval:Interval; qb:concept sdmx-concept:refPeriod .

Note:

rdfs:range is an instance of rdf:Property that is used to state that the values of a property are

instances of one or more classes.

The triple P rdfs:range C states that P is an instance of the class rdf:Property, that C is an

instance of the class rdfs:Class and that the resources denoted by the objects of triples whose

predicate is P are instances of the class C.












http://www.w3.org/TR/rdf-schema/



Components definition Region (unitary authority):

• Reuse of Predefined concept in the SMDX-COG, refArea

• For this example, the Ordanance Survey Administrative geography ontology

is used. More details can be found at:

http://data.ordnancesurvey.co.uk/ontology/admingeo/UnitaryAuthority

eg:refArea a rdf:Property, qb:DimensionProperty; rdfs:label "reference area"@en; rdfs:subPropertyOf sdmx-dimension:refArea; rdfs:range admingeo:UnitaryAuthority; qb:concept sdmx-concept:refArea .

Sex:

• Direct use of SMDX-COG component, sdmx-dimension:sex

Components definition Measure:

• Use of the default sdmx-measure:obsValue

• It is recommended to use a specific measure corresponding to the phenomenon

being observed.

• sdmx-measure:obsValue is defined by: http://sdmx.org/wp-content/uploads/2009/01/01_sdmx_cog_annex_1_cdc_2009.pdf

eg:lifeExpectancy a rdf:Property,

qb:MeasureProperty; rdfs:label "life expectancy"@en; rdfs:subPropertyOf sdmx-measure:obsValue; rdfs:range xsd:decimal .

Components definition Unit measure attribute:

• Plain decimal value

• Define what units it is measured in (years)

• For this example, we can use the predefined sdmx-attribute:unitMeasure

• Use of a common thesaurus of units of measures. For this example, a Dbpedia

resource is used, http://dbpedia.org/resource/Year

We can now define the structure of the data set. However, before we define the

structure of the data set we should note that:

• The dimensions can be usefully ordered

• There is only one attribute, the unit measure, and this is required

• The attribute will be attached at the level of the data set, since it is only one

http://dbpedia.org/resource/Year

Data Structure Definition (DSD) eg:dsd-le a qb:DataStructureDefinition;

# The dimensions

qb:component [qb:dimension eg:refArea; qb:order 1];

qb:component [qb:dimension eg:refPeriod; qb:order 2];

qb:component [qb:dimension sdmx-dimension:sex; qb:order 3];

# The measure(s)

qb:component [qb:measure eg:lifeExpectancy];

# The attributes

qb:component [qb:attribute sdmx-attribute:unitMeasure; qb:componentAttachment qb:DataSet;] .

Notes to remember:

• The URI of the DSD can be reused across different datasets with the same

structure

• The component properties can also be reused, but across different DSDs

• The component specifications are only useful within the scope of a

particular DSD

• Multiple observed values are allowed to be attached to an individual

observation, by declaring multiple qb:MeasureProperty components in the

DSD and attach an instance of each property to the observation within the

data set. However if one measure is applied to an observation, we can

distinguish which measure applies to the observation using the

qb:measureType dimension component.

Dataset and Observations

To represent the entire dataset (the collection of observations) a resource is defined, the qb:DataSet

A link between the DSD and the DataSet is created via the qb:structure property

eg:dataset-le1 a qb:DataSet;

rdfs:label "Life expectancy"@en;

rdfs:comment "Life expectancy within Welsh Unitary authorities - extracted from Stats Wales"@en;

qb:structure eg:dsd-le ;

.

• Each observation is represented as an instance of a qb:Observation

• The values for each of the attributes, dimensions and measurements are

attached directly to the observation

• The observation is linked to the containing data set via

the qb:dataSet property.

Observations eg:o1 a qb:Observation;

qb:dataSet eg:dataset-le1 ;

eg:refArea admingeo:newport_00pr ;

eg:refPeriod <http://reference.data.gov.uk/id/gregorian-interval/2004-01-01T00:00:00/P3Y> ;

sdmx-dimension:sex sdmx-code:sex-M ;

sdmx-attribute:unitMeasure <http://dbpedia.org/resource/Year> ;

eg:lifeExpectancy 76.7 ; .

eg:o2 a qb:Observation;


eg:refArea admingeo:cardiff_00pt ;







eg:refArea admingeo:monmouthshire_00pp ;





...

Removing repeated component We notice that the measure is attached to each observation and its repeated.

The unit of measure is not changed between the different observations.

To remove redundancy we attached the attribute at the level of the dataset.

Our example will now turned to:

Before

After





.





sdmx-attribute:unitMeasure <http:/dbpedia.org/resource/Year>;

.

Therefore it can be skipped by the Observations.

Removing repeated component eg:o1 a qb:Observation;



















...

Slices

Slices allow us to group subsets of observations together

We first define the structure of the slices we want by associating a "slice

key" with the DSD, by creating a qb:SliceKey which lists the component

properties (which must be dimensions) which will be fixed in the slice.

The key is attached to the DSD using qb:sliceKey.

For example “male life expectancy observations for 2004-6” regions. In this

case, we keep the dimensions sex and time fixed.

eg:sliceByRegion a qb:SliceKey;

rdfs:label "slice by region"@en;

rdfs:comment "Slice by grouping regions together, fixing sex and time values"@en;

qb:componentProperty eg:refPeriod, sdmx-dimension:sex .

eg:dsd-le-slice1 a qb:DataStructureDefinition;


[qb:dimension eg:refPeriod; qb:order 2];

[qb:dimension sdmx-dimension:sex; qb:order 3];

[qb:measure eg:lifeExpectancy];

[qb:attribute sdmx-attribute:unitMeasure;

qb:componentAttachment qb:DataSet;] ;

qb:sliceKey eg:sliceByRegion .

Slices

In the instance data then slices are represented by instances of qb:Slice which

link to the observations in the slice via qb:observation and to the key via

the qb:sliceStructure. Data sets indicate the slices they contain by means

of qb:slice.

Slices eg:dataset-le2 a qb:DataSet;



qb:structure eg:dsd-le-slice2 ;


qb:slice eg:slice2; .

eg:slice2 a qb:Slice;

qb:sliceStructure eg:sliceByRegion ;



qb:observation eg:o1b, eg:o2b; eg:o3b, ... .

eg:o1b a qb:Observation;






Slices eg:o2b a qb:Observation;






eg:o3b a qb:Observation;






...

• However, looking at the observations we can see that we have redundancy,

since we are repeating the dimension values on the individual observations:

the eg:refPeriod and sdmx-dimension:sex.

• Redundancy can be reduced by declaring different attachment levels for

the dimensions at the DSD.

Slices Before



[qb:dimension eg:refPeriod; qb:order 2];

[qb:dimension sdmx-dimension:sex; qb:order 3];


[qb:attribute sdmx-attribute:unitMeasure; qb:componentAttachment qb:DataSet;] ;


After


qb:component

[qb:dimension eg:refArea; qb:order 1];

[qb:dimension eg:refPeriod; qb:order 2; qb:componentAttachment qb:Slice];

[qb:dimension sdmx-dimension:sex; qb:order 3; qb:componentAttachment qb:Slice];


[qb:attribute sdmx-attribute:unitMeasure; qb:componentAttachment qb:DataSet;] ;


Slices Therefore, the observations that belong to slices now can be written in the following way:

eg:o1c a qb:Observation;














...

• The Data Cube vocabulary allows slices to be nested. We can declare

multiple slice keys in a DSD and it is possible for one slice key to be a

narrower version of another, represented using qb:subSlice.

Creating appropriate URIs

Schema – Structural components

e.g., http://linkedstatistics.gr/schema/

http://linkedstatistics.gr/schema/PopulationCensus2011/

Vocabulary

e.g. http://linkedstatistics.gr/dic/

http://linkedstatistics.gr/dic/geocode/

http://linkedstatistics.gr/dic/geocode#010101

◦ Dataset - Observation Values

e.g. http://linkedstatistics.gr/data/

http://linkedstatistics.gr/data/PopulationCensus2011#010101

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